Methods and systems for providing a combination of media data and metadata

ABSTRACT

A method of providing a combination of video data ( 37 ) and metadata ( 34 ) includes obtaining a sequence ( 23 ) of images captured by a video camera ( 5 ). At least one signal ( 24 ) is extracted from the sequence ( 23 ) of images, wherein each extracted signal ( 24 ) characterizes local temporal variations in at least one of light intensity and color. At least one video compression technique is applied on image data of images from the sequence ( 23 ) to obtain compressed video data ( 37 ). The extracted signals ( 24 ) are extracted from images in a state prior to the application of the at least one compression technique to image data from those images. The compressed video data ( 37 ) is provided with metadata ( 34 ) for characterizing at least one process in a subject represented in at least part of the images, which process causes local temporal variations in at least one of color and intensity of light captured from the subject. The metadata ( 34 ) is at least based on at least one of the extracted signals ( 24 ).

FIELD OF THE INVENTION

The invention relates to a method of providing a combination of mediadata and metadata, a system for providing a combination of media dataand metadata. The invention also relates to a signal including acombination of compressed video and metadata, wherein the compressedvideo is obtainable by applying at least one video compression techniqueon image data of images from a sequence of images. The invention furtherrelates to a method of processing such a signal, a system for processingsuch a signal, and a computer program.

BACKGROUND OF THE INVENTION

US 2009/0192961 A1 describes a system for adapting the bit rate of amedia stream based on user interest. Collected biometric data can beused to determine a user's emotional interest and optionally adjust thebit rate of media and/or present navigation options to one or moreselected portion of the stored media. Biometric data can include heartrate, respiratory rate, galvanic skin response, pupil dilation, bloodpressure, body temperature and the like. Biometrics can be collectedfrom sensors, which can include electrodermal sensors, microphones,thermometers, accelerometers and the like. In an embodiment, changes inuser interest can trigger a variable bit rate encoder to adjust the bitrate processing of captured audio/video based on configuration options.For example, a digital camera can obtain biometric data during picturecapture. When user interest is detected as high, the image resolutionand megapixel count can be increased, storing the picture as a highfidelity image. Collected biometric data can be stored as metadata inthe images for use in playback and navigation.

A problem of the known system is that it is limited to the biometricdata that can be obtained at the time of capture. Only the biometricdata characterizing the person attached to the sensor is obtained.Additional biometric sensors of the described type are required for eachadditional person, and each person must co-operate.

SUMMARY OF THE INVENTION

It is desirable to provide a method, system, signal and computer programof the types referred to above that allow for the efficient provision ofvideo data with metadata characterizing processes in subjectsrepresented in the video.

To this end, according to a first aspect, there is provided a method ofproviding a combination of video data and metadata, including:

obtaining a sequence of images captured by a video camera;

extracting at least one signal from the sequence of images, wherein eachextracted signal characterizes local temporal variations in at least oneof light intensity and color;

applying at least one video compression technique on image data ofimages from the sequence to obtain compressed video data,

wherein at least one of the signals is extracted from images in a stateprior to the application of the at least one compression technique toimage data from those images; and

providing the compressed video data with metadata for characterizing atleast one process in a subject represented in at least part of theimages,

which process causes local temporal variations in at least one of colorand intensity of light captured from the subject,

wherein the metadata is at least based on at least one of the extractedsignals.

A subject represented in a sequence of images will generally be a livingsubject, but may be an inanimate object. A process causing localtemporal variations in at least one of light intensity and color willgenerally be an internal process independent of any movement of anyexternally visible part of the subject. It may, however, be a process ofinternal movement (e.g. rotation or reciprocal movement of a part of asubject relative to a reference frame fixed to the subject) of a visiblepart of the subject in some applications. In the case of a livingsubject and an internal process, the extracted signals carry informationcorresponding to at least one biometrical signal.

By providing compressed video data, the method is relatively efficient.Because compressed video data, in particular compressed video dataobtained using predictive coding is generally no longer suitable forextracting signals representative of local temporal variations in atleast one of light intensity and color, which might be used to obtaindata characterizing at least one biological phenomenon in a subjectrepresented in the image, the method provides metadata that correspondsto or is suitable for use in obtaining such data characterizing abiological phenomenon. The method is based on the extraction of at leastone signal from the sequence of images prior to compression, so that thesmall-scale variations in intensity and/or color that are caused byprocesses in a subject represented in at least part of the images arestill represented in the extracted signals. By being based on suchextracted signals, the method can be used to obtain data characterizingmultiple persons represented in the sequence of images, namely byextracting multiple signals, without having to provide additionalsensors. The method is also essentially independent of living subjects'willingness to co-operate, since no sensors placed on the body arerequired. The method is suitable e.g. in surveillance applications toprovide biometric data in combination with compressed video. Thebiometric data can be used to identify portions of the compressed videorequiring closer scrutiny. Because the video is compressed, a datatransmission network with a relatively low capacity can be used forcollecting video and metadata from camera systems. The system can easilybe arranged to enable short-term responses to events signaled by themetadata by persons having access to the compressed video to determinethe nature of the event.

An embodiment of the method includes adapting the application of the atleast one compression technique in dependence on an outcome of ananalysis of data at least based on obtained parts of at least one of theextracted signals.

This embodiment can be used to provide a solution to the problem thatmore metadata may be required if there are more persons represented inthe sequence of images and biometric data relating to each of themindividually is to be recoverable from the metadata. The amount ofincluded metadata can be varied according to need (amount ofinformation) whilst keeping the total amount of data (compressed videoand metadata) within bounds. Alternatively or additionally, thisembodiment can be used to apply more or less compression on certainspatial parts of the sequence of images, depending on whether thoseparts represents subjects of interest or not. For example, the extractedsignals can be used to determine where the faces of living personsrepresented in the images are located. These spatial parts of the imagescan be encoded such as to preserve more detail. The same is true wherepredictive coding is used as part of the compression technique. If it isdetermined that parameters characterizing the process vary rapidly intime during intervals corresponding to certain sections of the sequenceof images, then less interpolation can be applied to encode thesesections as part of the compression.

An embodiment of the method includes, whilst obtaining the sequence ofimages, causing adjustments of parameters of a process of capturing theimages using at least one camera in dependence on an outcome of ananalysis of data at least based on obtained parts of at least one of theextracted signals.

This embodiment makes it possible to use a relatively cheap camerawithout generating unreliable data characterizing the processes in asubject represented in the sequence of images. Instead of having to usea high-definition camera, parameters can be adjusted so that thecomponents of the extracted signal or signals carrying the informationrelating to the process in the subject are more clearly present in theextracted signals. In one variant of this embodiment, parametersaffecting the settings of an optical system used to focus light onto asensor array are adapted. Thus, it is possible to zoom in to capturemore information relating to certain parts of a scene represented in thesequence of images. The number of pixels used to create the extractedsignal or signals can thus be increased. Alternatively more extractedsignals carrying information relating to the same process can begenerated, which will then result in a more reliable consensus signal orvalue characterizing the process in the subject. In another variant, atleast one parameter of a system for converting light intensity intodiscrete pixel values is adjusted in dependence on an outcome of theanalysis of the data at least based on obtained parts of at least one ofthe extracted signals. Examples of such parameters include the gain anddiscretisation threshold of an image sensor array. In this embodiment,the pixel values carry more reliable information representative ofsmall-scale variations in color or intensity, typically due to internal(especially biological) processes. Other parameters that can be adjustedinclude exposure time and frame rate (typically parameters of a systemfor converting light intensity into discrete pixel values, since digitalcameras will generally not have mechanical shutters).

In an embodiment, the method is carried out by a processing systemincluded in a camera.

This means that the processing system is included in the same housing asthe image sensor array. This embodiment largely avoids the communicationof uncompressed video data, and is therefore relatively cheap toimplement. In a particular variant, the camera is provided with at leastone network interface, so that the combination of video data andmetadata is transmittable over a network by the camera itself. Thiscombination is in one embodiment a multiplex of compressed video and astream of metadata synchronized with the compressed video stream.Suitable cameras (so-called IP cameras) already exist. This variant ofthe method merely requires them to be suitably configured to carry outthe method.

In an embodiment, the metadata includes at least one signalcharacterizing local temporal variations in at least one of lightintensity and color in the sequence of images.

Thus, the metadata includes signals essentially similar to the extractedsignals. They may, however, be the result of an operation combining twoor more of the extracted signals, e.g. an averaging or clusteringoperation. In this embodiment, the system providing the combination ofmetadata and compressed video need not carry out the processingnecessary to arrive at accessible information characterizing theprocesses in the subject in a concise way. This type of processing iscarried out by an external system arranged to process the combination ofcompressed video data and metadata. Accordingly, the type of processingcan be varied. Moreover, the system providing the combination ofmetadata and compressed video can be simpler. One expensive system canprocess the compressed video data and metadata provided by severalcameras, for example.

According to another aspect of the invention, there is provided a systemfor providing a combination of video data and metadata, including

at least an interface to a camera for capturing a sequence of images;

a video data processing system, configured to:

apply at least one video compression technique on image data of imagesfrom the sequence to obtain compressed video data,

extract at least one signal from the sequence of images, each extractedsignal characterizing local temporal variations in at least one of lightintensity and color and

to generate metadata for characterizing at least one process in at leastone subject represented in at least part of the images,

wherein the extracted signals are extracted from images in a state priorto the application of the at least one compression technique to imagedata from those images and

wherein the metadata characterizes processes causing local temporalvariations in at least one of color and intensity of light captured fromthe subject and the metadata are at least based on at least one of theextracted signals; and

an output interface for providing the compressed video data with themetadata.

In an embodiment, the system is configured to carry out a methodaccording to the invention.

According to another aspect of the invention, there is provided a signalincluding a combination of compressed video and metadata, wherein thecompressed video is obtainable by applying at least one videocompression technique on image data of images from a sequence of imagesand the metadata includes at least one signal characterizing localtemporal variations in at least one of light intensity and color in thesequence of images.

A system arranged to receive and process the signal can obtaininformation characterizing processes in subjects represented in theimages. Because the metadata includes at least one signal characterizinglocal temporal variations in at least one of light intensity and colorin the sequence of images, various types of such information can beobtained. For example, the extracted signals can be used to determineeither the heart rate or the respiration rate of a living subjectrepresented in the images. Only one type of metadata is required forthis, namely the extracted signals. One effect is that the signal can begenerated by relatively uncomplicated camera systems. Another effect isthat it is not necessary to achieve standardization of a large number ofdifferent types of metadata (i.e. agreement on codes indicating thevariable that a particular numerical value in the metadata represents).One type of metadata is sufficient. In a variant, the metadata willindicate the spatial location to which a particular signalrepresentative of local variations in at least one of light intensityand color pertains.

In an embodiment, the signal is obtainable by executing a methodaccording to the invention.

According to another aspect of the invention, there is provided a methodof processing a signal according to the invention, including calculatingat least one value of a parameter characterizing at least one process ina subject represented in at least part of the sequence of images, whichprocess causes local temporal variations in at least one of color andintensity of light captured from the subject, using as input at leastone of the signals characterizing local temporal variations in at leastone of light intensity and color in the sequence of images.

According to a further aspect of the invention, there is provided asystem for processing a signal including a combination of compressedvideo and metadata, including:

an interface for obtaining a signal according to the invention and

a data processing system for calculating at least one value of aparameter characterizing at least one process in a subject representedin at least part of the sequence of images, which process causes localtemporal variations in at least one of color and intensity of lightcaptured from the subject, using as input at least one of the signalscharacterizing local temporal variations in at least one of lightintensity and color in the sequence of images.

According to yet another aspect of the invention, there is provided acomputer program including a set of instructions capable, whenincorporated in a machine-readable medium, of causing a system havinginformation processing capabilities to perform a method according to theinvention.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention will be described in further detail with reference to theaccompanying drawings, in which:

FIG. 1 is a schematic block diagram of a system comprising a camerasystem for generating a signal combining a compressed video stream withmetadata and a system for processing this combined signal;

FIG. 2 is a flow chart illustrating some steps in a method carried outby the system for generating the signal;

FIG. 3 is a flow chart illustrating in detail a step of generatingsignals representative of local temporal variations in at least one ofintensity and color in a sequence of images as part of an embodiment ofthe method illustrated in FIG. 2;

FIG. 4 is a flow chart giving an outline of a first method of processingthe combined signal; and

FIG. 5 is a flow chart giving an outline of a second method ofprocessing the combined signal.

DETAILED DESCRIPTION

A system comprising a first and second camera system 1,2, a network 3and a video signal processing system 4 is used here to explain methodsof providing and processing a combination of compressed video data andmetadata. In the illustrated embodiment, the first camera system 1comprises a single camera 5 with a network interface 6. In anotherembodiment, the first camera system 1 comprises a combination of acomputing device and a camera connected thereto, e.g. via a direct link,and operating under the control of the computing device, which alsoprocesses raw uncompressed video data to generate a combination ofcompressed video data and metadata.

The second camera system 2 can have the same build-up as the firstcamera system 1, and is not illustrated in more detail for this reason.

The camera 5 includes an image sensor array 7, e.g. a CCD or CMOS sensorarray of a known type. It further includes an optical system 8 forfocusing light from a scene onto the image sensor array 7. The opticalsystem 8 will generally include one or more lenses, filters, a diaphragmand the like, each of which can be adjusted under the control of acamera processor 9. Similarly, the camera processor 9 can set parametersof the image sensor array 7, including integration time, gain,discretisation threshold, etc. It is noted that where reference is madeherein to sequence of images, this can include combinations of sequencesof images in different color channels. Thus, an image can mean thecombination of two or more, e.g. three, image frames, each an array ofpixel values representing the captured intensity of light in aparticular range of the electromagnetic spectrum. It is further notedthat the camera 5 can be arranged to operate in either the visible orthe invisible part of the electromagnetic spectrum, or in both. Thus,images can consist of or comprise an array of pixel values representingcaptured intensities in the infra-red part of the spectrum.

In the illustrated embodiment, a video encoder 10 is provided tocompress raw image data, and thereby generate compressed video. However,the processor 9 is able to process the raw uncompressed image data aswell, to which end a volatile memory unit 11 is provided.

In other embodiments, the functionality of the components of the camera5 is combined into fewer separate devices or distributed over moredevices than are illustrated in FIG. 1.

The illustrated camera 5 is provided with user controls 12 and a display13.

The camera 5 and the second camera system 2 are each configured toprovide a data stream comprising a compressed video data stream and ametadata data stream. The compressed video data stream and the metadatadata stream are provided with a common time base, so that metadata andcompressed video are synchronized. In a particular embodiment, themetadata data stream and the compressed video data stream are providedin a multiplex.

A particular application is used here by way of example, in which thecamera 5 is used to provide a compressed video data stream representingone or more persons in combination with a metadata data stream carryinginformation that either directly characterizes one or more biologicalprocesses in the persons represented or allows the video signalprocessing system 4 to derive such information. The camera 5 generatesthe metadata by first extracting one or more first signals, eachrepresentative of local temporal variations in either light intensity orcolor, or both, from a sequence of uncompressed images. Thus, theprocesses to be described herein are suitable for obtaining metadata onbiological processes that cause a variation in the color or intensity oflight reflected or passed through a living person. It is particularlyused to obtain metadata on (quasi-) periodic biological processes suchas heart beat and respiration. However, other phenomena, such asperspiration, can also be characterized, in particular by focusing on anappropriate range within the electromagnetic spectrum.

In one embodiment, to be described more fully herein, the camera 5 andthe second camera system 2 provide only metadata directly representativeof signals representative of local variations in at least one of lightand color, meaning that such signals can be fully reconstructed from themetadata, or at least be reconstructed but for a phase difference. Inanother embodiment, the metadata is representative of parameter valuesdirectly characterizing the biological phenomenon. In this embodiment,signals representative of local variations in at least one of light andcolor on which the metadata is based can no longer be reconstructed fromthe metadata. Providing metadata representative of parameter valuesdirectly characterizing the biological phenomenon requires moreintelligence in the camera 5 but it means that the size of the metadatais smaller. On the other hand, the video signal processing system 4 onlyhas access to the biological information that the camera 5 has beenprogrammed to provide (e.g. the heart rate values of the personsrepresented in the compressed video stream but not the respiration ratevalues). In addition, there must be a protocol to enable the videosignal processing system 4 to determine the nature of the variable towhich numerical values in the metadata relate.

The video signal processing system 4 can be implemented in the form of ageneral purpose computer. Thus, in FIG. 1, it is shown as comprising anetwork interface 6, central processing unit 15 (CPU) and main memory16, user input device 17, mass-storage device 18 and graphics unit 19.It is connected to two display devices 20,21 by way of example. In analternative embodiment a separate decoder device for decompressing thereceived compressed video stream can be provided, but in the illustratedembodiment this is done by the CPU 15 or the graphics unit 19. In theillustrated embodiment, the decompressed video can be shown on one ofthe display devices 20,21, and information relating to biologicalprocesses in living subjects represented in the video can be shown onthe other. This display can be in the form of a graphical displayincluding a graphical representation corresponding to the scene beingshown in the video, with the biological information shown at screenpositions corresponding substantially to the screen position at whichthe subject to which it relates is represented in the video. In analternative embodiment, the biological information is overlaid on thevideo. In one embodiment, it is overlaid in response to input providedvia the user input device 17. In a further embodiment, the video fromthe camera 5 and from the second camera system 2 can be shown onseparate ones of the two display devices 20,21, e.g. to implement asurveillance system for security purposes. Biological information can beused to highlight scenes that are potentially of interest, e.g. thoserepresenting persons with elevated heart rates or perspiration.

Turning to FIG. 2, an example of a method of providing a combination ofcompressed video data and metadata as might be carried out by theprocessor 9 in the camera 5 will now be described.

With each obtained next image (step 22), a sub-sequence 23 of alreadyobtained images is updated. In the illustrated embodiment, the nextpoint in each of a set of first signals 24 a-n is then obtained (step25) using a remote photoplethysmographic method.

One way in which first signals can be obtained is illustrated in outlinein FIG. 3. A sequence 26 of images—this may be a combination of two orthree sequences of images in different color channels—is obtained (step27).

Then, in an optional but useful step, a correction is applied to theimages 26. This can involve subtracting variations in overall lightintensity levels (determined e.g. by averaging over all pixels in animage, indeed over all pixels of all corresponding image frames indifferent color channels) from the pixel values in the images. The aimis to remove variations due to background lighting or camera movement asmuch as possible, so as to isolate local variations in spatial regionsof the images due to processes in the subjects represented in theimages.

Then (step 29), a grid defining a plurality of measurement zones, eachencompassing a plurality of pixel points, is laid over the images 26.

Next (step 30), a first set of extracted signals 31 a-n is established,each value of an extracted signal 31 a-n being based on a combination ofpixel values from one of the measurement zones. This can be an average,for example. It can also be the mean value. It can also be a weightedaverage with different weights being used for pixel values fromdifferent color channels. Thus, for example, green can be overweighted,because it is especially sensitive to variations in the level ofoxyhaemoglobin in skin tissue. Similarly, blue can be given extraweight, because it is sensitive to variations in the water content ofskin tissue and to variations in the moisture level of the skin surface,and thus representative of pulsating blood plasma flow and changinglevels of perspiration. It is noted that, instead of carrying outspatial averaging, clustering can be carried out. That is to say, asignal or signal segment representative of intensity variations isgenerated for each of multiple pixel locations in a measurement zone,and these signals or signal segments are then clustered to generate asingle extracted signal 31 for each measurement zone.

In the illustrated embodiment, a second set of signals 32 a-n isgenerated (step 33). Each signal 32 a-n is representative of variationsin a corresponding one of the first set of signals 31. The second set ofsignals 32 can be generated by centering the signals 31 on their mean oraverage value. In alternative embodiments, a different or furthertechnique for obtaining small signal variations is carried out, e.g.high-pass or band-pass filtering.

As illustrated, the signals 32 a-n of the second set correspond to thefirst signals 24 a-n. In other embodiments, a selection can be made. Forexample, those of the signals 32 a-n of the second set with little or noinformation content can be discarded.

It is noted that an alternative embodiment (not shown in detail) ispossible, in which the grid is not used. Instead, image segmentation isused to identify those parts of the images corresponding to livingpersons. Then, at least one measurement zone is selected within eachregion of interest. Regions of interest or measurement zones are trackedthrough the image sequence 26, and a signal is extracted from eachmeasurement zone in the manner explained for the embodiment of FIG. 2.This embodiment is slightly more complicated, because the processor 9 inthe camera 5 must be capable of carrying out the image segmentation, aswell as algorithms for recognizing certain types of region of interest(e.g. a face recognition algorithm) and algorithms for trackingmeasurement zones and/or regions of interest through a sequence ofimages. However, where, for example, the second camera system 2comprises a camera and a computing device, this embodiment could befeasible and would have the effect that fewer first signals 24 a-n aregenerated, which are moreover all likely to be relevant tocharacterizing phenomena causing local variations in light intensityand/or color. An algorithm for face recognition is described in Viola,P. and Jones, M. J., “Robust real-time object detection”, Proc. IEEEWorkshop on statistical and computational theories of vision, 13 Jul.2001. A tracking algorithm is described in De Haan et al., “True-motionestimation with 3-D recursive search block matching”, IEEE Transactionson circuits and systems for video technology, 3 (5), October 1993, pp.368-379.

After the step 25 (FIG. 2) of obtaining further points of the firstsignals 24 a-n, new values in a stream 34 of metadata can be created(step 35). The metadata is in a pre-determined format, which can beproprietary or standardized.

As mentioned, in one embodiment, this step 35 entails further processingof the first signals 24 a-n, or the sections thereof obtained thus far,in order to obtain values of parameters that directly characterize thephenomenon of interest. For example, the first signals 24 a-n can betransformed into the frequency domain using a sliding window, in orderto obtain a spectrum of each first signal at successive points in time.The value of the dominant frequency in at least a limited range of thespectrum is determined so as to obtain a time-varying signalrepresentative of the heart rate or respiration rate, for example. Thesevalues can then be coded as metadata. In an embodiment, the values areassociated with data identifying a spatial region in the images, so thatthe heart rate or respiration rate values can be associated withrespective ones of several living beings represented in the sequence ofimages.

In the embodiment described herein in more detail, data directlyrepresentative of the first signals 24 a-n are encoded into themetadata, together with associated data identifying the location of themeasurement zone from which the first signal 24 a-n concerned wasextracted. The data identifying the location of the measurement zone maybe implicit, e.g. in the order in which values are recorded in a tablecomprised in the metadata.

The image data of the images in the sub-sequence 23 obtained thus farare compressed (step 36) to obtain compressed video frames 37. In theillustrated embodiment of the method, at least one interframecompression technique is applied to the images in the sub-sequence 23obtained thus far. Moreover, at least one lossy compression technique isused. Generally, such compression techniques will remove small-scaleintensity and color variations. Thus, it will generally not be possibleto extract signals representative of temporal variations in at least oneof intensity and color caused by internal processes in a subjectrepresented in the compressed video frames 37. For this reason, theextraction step 25 and compression step 36 are carried out in parallelon the obtained uncompressed images 23, or the extraction step 25 iscarried out first.

The stream 34 of metadata and the compressed video frames 37 aremultiplexed into a single data stream (step 38). Each is referred to acommon time base, so that the first signals 24 a-n or time-varyingvalues of a parameter characterizing the internal process causing thetemporal variations characterized by the first signals 24 a-n aresynchronized with the compressed video stream. Suitable formats for thecombined data stream are provided by the MPEG-4 systems standard(ISO/IEC 14496-1), for example. The steps of the method illustrated inFIG. 2 and described above make up an independent and compete firstembodiment of a method of providing a combination of compressed videodata and metadata.

Certain additional features of a second embodiment that provide furthereffects are also illustrated in FIG. 2.

In this embodiment, a further step 39 is carried out that involvesanalysis of parts of the first signals 24 a-n obtained thus far. In theillustrated embodiment, this step 39 is carried out whilst thecompression (step 36) is ongoing, and also whilst the acquisition ofimages (step 22) is ongoing.

This is done because the outcome of the analysis is used to cause anadjustment of at least one parameter of a process of capturing theimages (step 40) as well as to cause (step 41) an adaptation of at leastone compression technique being applied (step 36) in parallel.

Various types of analysis and adaptation can be used. In one embodiment,the analysis is of the first signals 24 a-n directly. In anotherembodiment, part or all of a process of deriving information from thefirst signals 24 a-n that is characteristic of the internal processcausing the local temporal variations in intensity and/or color iscarried out, and the analysis is of the information derived in this way.For example, the analysis could be of the spectra of the first signals24 a-n.

In one embodiment, first signals 24 a-n or values characterizingrespective first signals 24 a-n are compared to each other. Thus, itcould be determined whether first signals 24 a-n have a common dominantfrequency to within a certain accuracy. In a sense, this is adetermination of how many different persons are represented in theimages. If there are several persons, then there is less scope forreducing the amount of metadata, so that the video compression rate willbe increased. This ensures that the overall amount of data sent acrossthe network 3 can stay within certain limits. If the dominant frequencyis only present in first signals 24 a-n associated with certain spatialregions of the images, then the compression can be lower in thoseregions than in other regions. This is because they are likely to be themost interesting regions to a human observer. In case of human subjects,these regions are likely to correspond to persons' bodies. If thedominant frequency changes rapidly in time, then an interframecompression technique can be adapted to use less prediction, becausethere are likely to be many changes in the scene represented by theimages 23, e.g. persons coming and going.

As far as the analysis in combination with the adjustment of parametersof the process of capturing the images 23 is concerned, these includeparameters corresponding to settings of at least one of the image sensorarray 7 and the optical system 8 that is used to focus light onto theimage sensor array 7. This means in particular that certain parts of thescene can be captured with a higher resolution, even though the pixelcount of the image sensor array 7 may be quite low. The relevantanalysis can be a determination of the signal-to-noise ratio and/or ofthe dynamic range of the first signals 24 a-n, for example. If thesignal-to-noise ratio is low, then the camera 5 can zoom in. If thedynamic range is low, then the quantization step of ananalogue-to-digital converter in the image sensor array 7 can be madesmaller, for example. Further possible analyses include a determinationof the consistency of the dominant frequency o the first signals 24 a-ncorresponding to the frequency of a biological phenomenon of interest(heart rate, respiration rate) or a determination of the frequencydistributions of transformations to the frequency domain of the firstsignals 24 a-n.

By adapting the image capturing process and/or the compression in thisway, there is implemented a closed feedback loop between the camera 5hardware used to capture images and a detector of biometric signals.Control parameters of the camera 5 are adjusted continuously andautomatically in order to keep the reliability of the detectedbiometrical signals at a constant high level.

In the example in which at least some of the first signals 24 a-n aredirectly encoded as metadata, the video signal processing system 4 cancarry out a method as illustrated in FIG. 4 or a method as illustratedin FIG. 5.

In the method illustrated in FIG. 4, the video signal processing system4 receives the multiplex (step 42), and separates the metadata from thecompressed video stream (step 43). The compressed video stream isdecompressed (step 44).

From the metadata, the video signal processing system 4 determines thefirst signals 24 a-n (step 45) together with associated informationidentifying the spatial location in the images with which the firstsignals 24 a-n are associated. A frequency transform (step 46) isapplied to determine the dominant frequency in at least a limited rangeof the spectrum of each first signal 24 a-n. This is done repeatedly,using a sliding window, so that the development of the dominantfrequency over time can be tracked. In particular, values of thedominant frequency can be associated with points in time correspondingto points in the decompressed video sequence obtained in the parallelstep 44. Thus, the frequency information and the decompressed video canbe displayed together (step 47) on one of the display devices 20,21. Inone embodiment, locations of living subjects represented in thedecompressed video within the display area are determined. Values of atleast one parameter characterizing a biological phenomenon aredetermined for each such person based on the information extracted fromthe metadata, and displayed overlaid on the decompressed video with avisible link to the location at which the person is represented. Inanother embodiment, alerts are provided whenever values of a parametercharacterizing an internal process in a subject represented in thedecompressed video meet certain criteria. Thus, for example, an audibleor visible alert can be provided whenever the video shows a person whoseheart rate values meet certain criteria, e.g. criteria indicative of amedical problem or of a security risk.

FIG. 5 shows a similar method of processing a signal including acombination of compressed video data and metadata, in particularmetadata directly representative of a plurality of first signals 24 a-nrepresentative of local variations in at least one of intensity andcolor. The metadata enables a determination of an associated imagelocation to be made for each first signal 24 a-n. Thus, the video signalprocessing system 4 is able to process each first signal 24 a-n todetermine at least one associated value of a parameter characterizingthe signal, and then generate a map of these parameter values.

In the illustrated example, the multiplex comprising the first signals24 a-n in the form of a metadata stream 34 and the compressed videostream is obtained (step 48). The metadata stream 34 is separated fromthe compressed video stream (step 49). Then, the first signals 24 a-nand the associated information linking each of them to a location in animage area are obtained 50. The first signals 24 a-n are each analyzedto determine the dominant frequency within at least a limited range oftheir spectrum (step 51). Then, in the illustrated embodiment, the phaseat the dominant frequency is determined for each first signal 24 a-n(step 52). In the illustrated embodiment, this information is used togenerate a phase map (step 53). In parallel, the compressed video streamis decompressed (step 54), and the decompressed video is also displayed(step 55). For example, the phase map can be displayed on one of thefirst and second display devices 20,21, and the decompressed video canbe displayed on the other.

In an alternative embodiment, one of the decompressed video and thephase map is used to enhance the display of the other. Thus, forexample, where the grid defining the measurement zones in the method ofFIG. 3 is relatively coarse, image segmentation carried out on thedecompressed video can be used to enhance the image provided by thephase map.

It is noted that, in the alternative in which the metadata provided tothe video signal processing system 4 no longer corresponds directly tothe first signals 24 a-n, one or both of the first and second camerasystems 1,2 can perform a method according to FIG. 4 or 5 subsequent tothe method of FIG. 3, so that the metadata stream 34 will carry datarepresentative of the dominant frequency within at least a limited rangeof the spectrum of each of the first signals 24 a-n, or will carry theinformation representative of a phase map. In either case, additionalinformation enabling internal processes in each of a number of subjectsrepresented in images captured by a camera to be characterized isprovided.

It should be noted that the above-mentioned embodiments illustrate,rather than limit, the invention, and that those skilled in the art willbe able to design many alternative embodiments without departing fromthe scope of the appended claims. In the claims, any reference signsplaced between parentheses shall not be construed as limiting the claim.The word “comprising” does not exclude the presence of elements or stepsother than those listed in a claim. The word “a” or “an” preceding anelement does not exclude the presence of a plurality of such elements.The mere fact that certain measures are recited in mutually differentdependent claims does not indicate that a combination of these measurescannot be used to advantage.

In an embodiment, instead of providing the first signals 24 a-n in thetime domain, information representative of a transformation of the firstsignals 24 a-n into the temporal frequency domain is provided in themetadata stream 34.

1. Method of providing a combination of video data (37) and metadata(34), including: obtaining a sequence (23) of images captured by a videocamera (5); extracting at least one signal (24) from the sequence (23)of images, wherein each extracted signal (24) characterizes localtemporal variations in at least one of light intensity and color;applying at least one video compression technique on image data ofimages from the sequence (23) to obtain compressed video data (37),wherein the at least one extracted signal (24) is extracted from imagesin a state prior to the application of the at least one compressiontechnique to image data from those images; and providing the compressedvideo data (37) with metadata (34) for characterizing at least oneprocess in a subject represented in at least part of the images, whichprocess causes local temporal variations in at least one of color andintensity of light captured from the subject, wherein the metadata (34)is at least based on at least one of the extracted signals (24). 2.Method according to claim 1, including adapting the application of theat least one compression technique in dependence on an outcome of ananalysis of data at least based on obtained parts of at least one of theat least one extracted signal (24).
 3. Method according to claim 1,including, whilst obtaining the sequence (23) of images, causingadjustments of parameters of a process of capturing the images using atleast one camera (5) in dependence on an outcome of an analysis of dataat least based on obtained parts of at least one of the extractedsignals (24).
 4. Method according to claim 1, wherein the method iscarried out by a processing system (9,11) included in a camera (5). 5.Method according to claim 1, wherein the metadata (34) includes at leastone signal (24) characterizing local temporal variations in at least oneof light intensity and color in the sequence (23) of images.
 6. Systemfor providing a combination of video data and metadata (34), includingat least an interface to a camera (5) for capturing a sequence (23) ofimages; a video data processing system (9,11), configured to: apply atleast one video compression technique on image data of images from thesequence (23) to obtain compressed video data (37), extract at least onesignal (24) from the sequence (23) of images, each extracted signal (24)characterizing local temporal variations in at least one of lightintensity and color and to generate metadata (34) for characterizing atleast one process in at least one subject represented in at least partof the images, wherein the at least one extracted signal (24) isextracted from images in a state prior to the application of the atleast one compression technique to image data from those images andwherein the metadata (34) characterizes processes causing local temporalvariations in at least one of color and intensity of light captured fromthe subject and the metadata (34) are at least based on at least one ofthe extracted signals (24); and an output interface (6) for providingthe compressed video data (37) with the metadata (34).
 7. (canceled) 8.Signal including a combination of compressed video and metadata (34),wherein the compressed video (37) is obtainable by applying at least onevideo compression technique on image data of images from a sequence (23)of images and the metadata (34) includes at least one signal (24)characterizing local temporal variations in at least one of lightintensity and color in the sequence (23) of images.
 9. (canceled) 10.Method of processing a signal according to claim 8, includingcalculating at least one value of a parameter characterizing at leastone process in a subject represented in at least part of the sequence(23) of images, which process causes local temporal variations in atleast one of color and intensity of light captured from the subject,using as input at least one of the signals (24) characterizing localtemporal variations in at least one of light intensity and color in thesequence (23) of images.
 11. System for processing a signal including acombination of compressed video (37) and metadata (34), including: aninterface (14) for obtaining a signal according to claim 8 and a dataprocessing system (15,16) for calculating at least one value of aparameter characterizing at least one process in a subject representedin at least part of the sequence (23) of images, which process causeslocal temporal variations in at least one of color and intensity oflight captured from the subject, using as input at least one of thesignals (24) characterizing local temporal variations in at least one oflight intensity and color in the sequence (23) of images.
 12. Computerprogram including a set of instructions capable, when incorporated in amachine-readable medium, of causing a system having informationprocessing capabilities to perform a method according to claim 1.